From cc6c4d807b107859f88947f7ec440666476fca26 Mon Sep 17 00:00:00 2001
From: Gael Guennebaud <g.gael@free.fr>
Date: Sat, 17 Jan 2009 14:05:01 +0000
Subject: add a sparse setter bench

---
 bench/sparse_setter.cpp | 224 ++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 224 insertions(+)
 create mode 100644 bench/sparse_setter.cpp

(limited to 'bench/sparse_setter.cpp')

diff --git a/bench/sparse_setter.cpp b/bench/sparse_setter.cpp
new file mode 100644
index 000000000..90112954f
--- /dev/null
+++ b/bench/sparse_setter.cpp
@@ -0,0 +1,224 @@
+
+//g++ -O3 -g0 -DNDEBUG  sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.005 -DSIZE=10000 && ./a.out
+//g++ -O3 -g0 -DNDEBUG  sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.05 -DSIZE=2000 && ./a.out
+// -DNOGMM -DNOMTL -DCSPARSE
+// -I /home/gael/Coding/LinearAlgebra/CSparse/Include/ /home/gael/Coding/LinearAlgebra/CSparse/Lib/libcsparse.a
+#ifndef SIZE
+#define SIZE 300000
+#endif
+
+#ifndef NBPERROW
+#define NBPERROW 12
+#endif
+
+#ifndef REPEAT
+#define REPEAT 1
+#endif
+
+#define EIGEN_GOOGLEHASH_SUPPORT
+#include <google/sparse_hash_map>
+#include "BenchSparseUtil.h"
+
+
+#define BENCH(X) \
+  timer.reset(); \
+  for (int _j=0; _j<NBTRIES; ++_j) { \
+    timer.start(); \
+    for (int _k=0; _k<REPEAT; ++_k) { \
+        X  \
+  } timer.stop(); }
+
+typedef std::vector<Vector2i> Coordinates;
+typedef std::vector<float> Values;
+
+EIGEN_DONT_INLINE Scalar* setrand_eigen_gnu_hash(const Coordinates& coords, const Values& vals);
+EIGEN_DONT_INLINE Scalar* setrand_eigen_google_dense(const Coordinates& coords, const Values& vals);
+EIGEN_DONT_INLINE Scalar* setrand_eigen_google_sparse(const Coordinates& coords, const Values& vals);
+EIGEN_DONT_INLINE Scalar* setrand_ublas_mapped(const Coordinates& coords, const Values& vals);
+EIGEN_DONT_INLINE Scalar* setrand_ublas_coord(const Coordinates& coords, const Values& vals);
+EIGEN_DONT_INLINE Scalar* setrand_ublas_compressed(const Coordinates& coords, const Values& vals);
+EIGEN_DONT_INLINE Scalar* setrand_mtl(const Coordinates& coords, const Values& vals);
+
+int main(int argc, char *argv[])
+{
+  int rows = SIZE;
+  int cols = SIZE;
+  //float density = float(NBPERROW)/float(SIZE);
+  
+  BenchTimer timer;
+  Coordinates coords;
+  Values values;
+  for (int i=0; i<cols*NBPERROW; ++i)
+  {
+    coords.push_back(Vector2i(ei_random<int>(0,rows-1),ei_random<int>(0,cols-1)));
+    values.push_back(ei_random<Scalar>());
+  }
+  std::cout << "nnz = " << coords.size()  << "\n";
+
+    // dense matrices
+    #ifdef DENSEMATRIX
+    {
+      timer.reset();
+      timer.start();
+      for (int k=0; k<REPEAT; ++k)
+        setrand_eigen_dense(coords,values);
+      timer.stop();
+      std::cout << "Eigen Dense\t" << timer.value() << "\n";
+    }
+    #endif
+
+    // eigen sparse matrices
+    {
+      timer.reset();
+      timer.start();
+      for (int k=0; k<REPEAT; ++k)
+        setrand_eigen_gnu_hash(coords,values);
+      timer.stop();
+      std::cout << "Eigen gnu hashmap\t" << timer.value() << "\n";
+    }
+    {
+      timer.reset();
+      timer.start();
+      for (int k=0; k<REPEAT; ++k)
+        setrand_eigen_google_dense(coords,values);
+      timer.stop();
+      std::cout << "Eigen google dense\t" << timer.value() << "\n";
+    }
+    {
+      timer.reset();
+      timer.start();
+      for (int k=0; k<REPEAT; ++k)
+        setrand_eigen_google_sparse(coords,values);
+      timer.stop();
+      std::cout << "Eigen google sparse\t" << timer.value() << "\n";
+    }
+    
+    #ifndef NOUBLAS
+    {
+      timer.reset();
+      timer.start();
+      for (int k=0; k<REPEAT; ++k)
+        setrand_ublas_mapped(coords,values);
+      timer.stop();
+      std::cout << "ublas mapped\t" << timer.value() << "\n";
+    }
+    {
+      timer.reset();
+      timer.start();
+      for (int k=0; k<REPEAT; ++k)
+        setrand_ublas_compressed(coords,values);
+      timer.stop();
+      std::cout << "ublas comp\t" << timer.value() << "\n";
+    }
+    {
+      timer.reset();
+      timer.start();
+      for (int k=0; k<REPEAT; ++k)
+        setrand_ublas_coord(coords,values);
+      timer.stop();
+      std::cout << "ublas coord\t" << timer.value() << "\n";
+    }
+    #endif
+    
+    
+    // MTL4
+    #ifndef NOMTL
+    {
+      timer.reset();
+      timer.start();
+      for (int k=0; k<REPEAT; ++k)
+        setrand_mtl(coords,values);
+      timer.stop();
+      std::cout << "MTL\t" << timer.value() << "\n";
+    }
+    #endif
+
+  return 0;
+}
+
+EIGEN_DONT_INLINE Scalar* setrand_eigen_gnu_hash(const Coordinates& coords, const Values& vals)
+{
+  using namespace Eigen;
+  SparseMatrix<Scalar> mat(SIZE,SIZE);
+  {
+    RandomSetter<SparseMatrix<Scalar>, StdMapTraits > setter(mat);
+    for (int i=0; i<coords.size(); ++i)
+    {
+      setter(coords[i].x(), coords[i].y()) = vals[i];
+    }
+//     std::cout << "check mem\n"; getchar();
+  }
+  return 0;//&mat.coeffRef(coords[0].x(), coords[0].y());
+}
+
+EIGEN_DONT_INLINE Scalar* setrand_eigen_google_dense(const Coordinates& coords, const Values& vals)
+{
+  using namespace Eigen;
+  SparseMatrix<Scalar> mat(SIZE,SIZE);
+  {
+    RandomSetter<SparseMatrix<Scalar>, GoogleDenseHashMapTraits> setter(mat);
+    for (int i=0; i<coords.size(); ++i)
+      setter(coords[i].x(), coords[i].y()) = vals[i];
+//     std::cout << "check mem\n"; getchar();
+  }
+  return 0;//&mat.coeffRef(coords[0].x(), coords[0].y());
+}
+
+EIGEN_DONT_INLINE Scalar* setrand_eigen_google_sparse(const Coordinates& coords, const Values& vals)
+{
+  using namespace Eigen;
+  SparseMatrix<Scalar> mat(SIZE,SIZE);
+  {
+    RandomSetter<SparseMatrix<Scalar>, GoogleSparseHashMapTraits> setter(mat);
+    for (int i=0; i<coords.size(); ++i)
+      setter(coords[i].x(), coords[i].y()) = vals[i];
+//     std::cout << "check mem\n"; getchar();
+  }
+  return 0;//&mat.coeffRef(coords[0].x(), coords[0].y());
+}
+#ifndef NOUBLAS
+EIGEN_DONT_INLINE Scalar* setrand_ublas_mapped(const Coordinates& coords, const Values& vals)
+{
+  using namespace boost;
+  using namespace boost::numeric;
+  using namespace boost::numeric::ublas;
+  mapped_matrix<Scalar> aux(SIZE,SIZE);
+  for (int i=0; i<coords.size(); ++i)
+  {
+    aux(coords[i].x(), coords[i].y()) = vals[i];
+  }
+//   std::cout << "check mem\n"; getchar();
+  compressed_matrix<Scalar> mat(aux);
+  return 0;// &mat(coords[0].x(), coords[0].y());
+}
+EIGEN_DONT_INLINE Scalar* setrand_ublas_coord(const Coordinates& coords, const Values& vals)
+{
+  using namespace boost;
+  using namespace boost::numeric;
+  using namespace boost::numeric::ublas;
+  coordinate_matrix<Scalar> aux(SIZE,SIZE);
+  for (int i=0; i<coords.size(); ++i)
+  {
+    aux(coords[i].x(), coords[i].y()) = vals[i];
+  }
+  compressed_matrix<Scalar> mat(aux);
+  return 0;//&mat(coords[0].x(), coords[0].y());
+}
+EIGEN_DONT_INLINE Scalar* setrand_ublas_compressed(const Coordinates& coords, const Values& vals)
+{
+  using namespace boost;
+  using namespace boost::numeric;
+  using namespace boost::numeric::ublas;
+  compressed_matrix<Scalar> mat(SIZE,SIZE);
+  for (int i=0; i<coords.size(); ++i)
+  {
+    mat(coords[i].x(), coords[i].y()) = vals[i];
+  }
+  return 0;//&mat(coords[0].x(), coords[0].y());
+}
+#endif
+
+#ifndef NOMTL
+EIGEN_DONT_INLINE void setrand_mtl(const Coordinates& coords, const Values& vals);
+#endif
+
-- 
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